ITM Web Conf.
Volume 54, 20232nd International Conference on Advances in Computing, Communication and Security (I3CS-2023)
|Number of page(s)||9|
|Published online||04 July 2023|
Simulated uav dataset for object detection
University Institute of Engineering and Technology, Panjab University, Chandigarh, India
* Corresponding author: firstname.lastname@example.org
Unmanned Aerial Vehicles (UAVs) have become increasingly popular for various applications, including object detection. Novel detector algorithms require large datasets to improve, as they are still evolving. Additionally, in countries with restrictive drone policies, simulated datasets can provide a cost-effective and efficient alternative to real-world datasets for researchers to develop and test their algorithms in a safe and controlled environment. To address this, we propose a simulated dataset for object detection through a Gazebo simulator that covers both indoor and outdoor environments. The dataset consists of 11,103 annotated frames with 27,412 annotations, of persons and cars as the objects of interest. This dataset can be used to evaluate detector proposals for object detection, providing a valuable resource for researchers in the field. The dataset is annotated using the Dark Label software, which is a popular tool for object annotation. Additionally, we assessed the dataset’s performance using advanced object detection systems, with YOLOv3 achieving 86.9 mAP50-95, YOLOv3-tiny achieving 79.5 mAP50-95, YOLOv5 achieving 82.2 mAP50-95, YOLOv7 achieving 61.8 mAP50-95 and YOLOv8 achieving 87.8 mAP50-95. Overall, this simulated dataset is a valuable resource for researchers working in the field of object detection.
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.